Search Results for "fps"

...Uses OpenCV and Tensorflow to perform realtime object detection locally for IP cameras. Use of a Google Coral Accelerator is optional, but highly recommended. The Coral will outperform even the best CPUs and can process 100+ FPS with very little overhead.

Claude Video Vision is a plugin designed for Claude Code that enables large language models to process and understand video content by transforming it into multimodal inputs the model can reason over. Instead of attempting to directly interpret raw video streams, the system extracts key frames using tools like ffmpeg and processes audio through transcription engines, converting both visual and auditory signals into structured inputs for the model. The result is a perception layer that feeds...

Cerberus is a First Person Shooter Game that incorporates machine learning techniques. The game utilizes Neural Networks to control fighting behavior and Reinforcement Learning to select high level tactics.

Emergent Mercenary is a 3D FPS with strategy overtones, and an excerise in emergent gaming. It should be easy to setup a scenario (e.g. hunt criminal) just by placing characters with certain AI into the game and see them interact.

Twang is a public-domain library for pathfinding in 2D polygonal environments, ideal for plugging in to a RPG, FPS, adventure, or RTS game.

Gamel (pronounced like camel) is a library written in C++ for use in games. Gamel includes common search and sort algorithms, easy-to-use networking methods, logging, 2D/3D distance calculation, entity classes for RPG and FPS games, pathfinding and more.

Qwen2.5-VL-3B-Instruct is a 3.75 billion parameter multimodal model by Qwen, designed to handle complex vision-language tasks in both image and video formats. As part of the Qwen2.5 series, it supports image-text-to-text generation with capabilities like chart reading, object localization, and structured data extraction. The model can serve as an intelligent visual agent capable of interacting with digital interfaces and understanding long-form videos by dynamically sampling resolution and...

Qwen2.5-VL-7B-Instruct is a multimodal vision-language model developed by the Qwen team, designed to handle text, images, and long videos with high precision. Fine-tuned from Qwen2.5-VL, this 7-billion-parameter model can interpret visual content such as charts, documents, and user interfaces, as well as recognize common objects. It supports complex tasks like visual question answering, localization with bounding boxes, and structured output generation from documents. The model is also...